ELPIS Lab
UH200B, Unity Hall
100 Institute Rd
Worcester, MA 01609
Wecome to the webpage of the Efficient Learning and Planning for Intelligent Systems (ELPIS) Lab!
The Lab has a broad interest in autonomous robotic systems capable of reasoning about and interacting with the physical world. The primary goal is to develop agents that are efficient, robust, and capable of learning from real-world interactions. Current research projects focus on the integration of classical planning algorithms and state-of-the-art machine learning techniques, aiming to advance 1) planning efficiency, 2) planning robustness, and 3) planning from visual inputs.
If you are interested in joining the Lab please see this page.
News
| May 15, 2025 | The first cohort of 8 M.S. students from the ELPIS Lab has graduated. Congratulations to everybody! |
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| Mar 15, 2025 | Prof. Chamzas was an invited panelist for the Future Faculty Fellows at Rice University. |
| Jan 24, 2025 | Our paper “Multi-layer Motion Planning with Kinodynamic and Spatio-Temporal Constraints” has been accepted to ACM Hybrid Systems: Computation and Control (HSCC) 2025! Congratulations to Abhiroop Ajith and Jeel Chatrola! |
| Nov 14, 2024 | Prof. Chamzas gave a talk at the UNH Robotics Seminar on “Learning and Planning for Robotic Manipulation: Bringing Theory to Practice.” |
| Aug 15, 2024 | Two new Ph.D. students, Abhiroop Ajith and Ali Golestaneh, are joining the ELPIS lab! |
| Aug 01, 2024 | The first paper of the ELPIS Lab titled “Expansion-GRR: Efficient Generation of Smooth Global Redundancy Resolution Roadmaps” has been accepted to IROS2024! Congrats Zhuoyun Zhong! |
| Jan 20, 2024 | Our preprint manuscript on Computing Efficient Global Redundancy Resolution Maps is available on Arxiv: |